docs: def innerprod(self, X):
          """
          Efficient computation of the inner product of a ktensor with another tensor
  
          Parameters
          ----------
          X : tensor_mixin
              Tensor to compute the inner product with.
  
          Returns
          -------
          p : float
              Inner product between ktensor and X.
          """
          N = len(self.shape)
          R = len(self.lmbda)
          res = 0
          for r in range(R):
              vecs = []
              for n in range(N):
                  vecs.append(self.U[n][:, r])
              res += self.lmbda[r] * X.ttv(tuple(vecs))
          return res